An application of cell-cluster theory to a rare gas crystal /|n[by] K. Westera. - 260 St. Catharines [Ont.] : Dept. of Physics, Brock University,

The Lennard-Jones Devonshire 1 (LJD) single particle theory for liquids is extended and applied to the anharmonic solid in a high temperature limit. The exact free energy for the crystal is expressed as a convergent series of terms involving larger and larger sets of contiguous particles called cell-clusters. The motions of all the particles within cell-clusters are correlated to each other and lead to non-trivial integrals of orders 3, 6, 9, ... 3N. For the first time the six dimensional integral has been calculated to high accuracy using a Lennard-Jones (6-12) pair interaction between nearest neighbours only for the f.c.c. lattice. The thermodynamic properties predicted by this model agree well with experimental results for solid Xenon.

Commodities and their fetishism

Many pr oblems present themselves in at tempting t o discuss Marx's noti on of the fetish characteristics of commodities. It has been argued that it is one of the central points of Marx's en tir e c or pus. 1 It has also been argued that it i s merely "a brilli an t s oci olog i cal genera lization l ! and, even furth er, that it is an Hi ndependent and separate entity, internally hardly related t o Marx's economic theory" .2 How could such a theory be understo od i n such drastically diff erent ways? Perhaps the clue is to be f ound somewhere in Marx' s discussion of the fetishism of commodities itself. Because of the difficulty in un derstanding fetishism , I intend t o examine what Marx himself has t o say first befor e dealing with any points related to the notion of fetishism. Thus , the first parts of this thesis will c onsist of l ong qu otations and repetition of what Marx has t o say. If a noti on may be called ' central' and yet 'hardly related' t o Marx's wor k at the same time, surely a clear examination of this section is necess ary. Aft er an examination of the initial secti ons of Cae ital ] I intend t G examine the f ollowing : the r e lation of fetishism t o the t he ory of alienati on; how one may regard f etishism as a pr oblem f or philosophy; and how, in f act, the theory of fetishism is of prime imp ortance f or an understan ding of Marx's wr itings. What I want to stress throughout is that with o u~ an understanding of what is inherent in the pr oduction of the commodity causing i t t o be necessarily fetishistic, it is practically imp ossible t o understand much of Marx's other writin gs. A commodity appears, at fir st sight, a very trivial thing and easi ly un derst ood. Itsanalysis shows that it i s , in r eality , a very queer thing , abo unding in ~taphysical s ubtleties and theological nic eties .

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

3-O-Demethylation of thebaine and the synthesis of a flacourtia aglycone from benzoic acid.

Two synthetic projects were embarked upon, both fraught with protecting group nuance and reaction selectivity. Transformations of the opiate skeleton remain a valuable tool for the development of new medicines. Thebaine, a biosynthetic intermediate in the expression of morphine, was converted in three steps to oripavine through two parallel modes. Through the use of protecting group manipulations, two irreversible scaffold rearrangements were avoided during aryl methyl ether bond cleavage. This chemistry constitutes a new path in manipulations of the morphinan scaffold through protective groups. A new compound family, the flacourtosides, contains an unusual cyclohexenone fragment. The newly described compounds show in preliminary tests antiviral activity against dengue and chikungunya. This aglycone was approached on three pathways, all beginning with the chemoenzymatic dihydroxylation of benzoic acid. A first attempt from a known vinyl epoxide failed to epimerize and cooperate under deprotective conditions. A second and third attempt made use of a diastereoselective dihydroxylation reaction, which was critical in reaching the correct stereochemistry and oxidation state. The methyl ester of the aglycone was prepared, constituting the first synthesis of the non-trivial natural product framework.